1. Field of the Invention
This invention generally relates to location and movement determination and, more particularly, to systems and methods for determining the spatial orientation of an inertial measurement unit (IMU).
2. Description of the Related Art
Inertial measurement units, also called inertial motion units, are devices that facilitate continuous computation of the orientation of the objects to which they are attached. By way of example, IMUs may be attached to human body limbs, robotic appendages, or aerial drones. IMUs typically have multiple single- or multi-axis sensors, such as gyroscopes, accelerometers, and magnetometers. Ideally, the accelerometer and magnetometer respectively measure the field strength of the local gravitational and magnetic fields produced by a reference object, such as Earth, and in turn produce sensor field strength readings. The gyroscope measures the rotational speed of the sensor relative to itself, producing a sensor rotational speed reading. The sensor field strength and rotational speed readings may be used singularly or in combination to compute the orientation of the IMU and its associated objects relative to the reference object. This object orientation is typically applied in an object motion tracking application.
Even well calibrated IMU sensors can exhibit measurement bias and measurement jitter, potentially causing noisy results in computed orientations. Further, gravitational and inertial accelerations both affect accelerometer output readings, causing an undeterminable offset in the sensor's reading from the actual direction of gravity, and therefore an uncertainty in the sensor's orientation relative to local gravitational up and down. Methods already exist for fusing IMU sensor values together to determine object orientation and mitigate sensor offsets and jitters, but they typically employ Kalman filters, which require matrix inversion and are computationally expensive. As a result, IMUs employing these methodologies typically require more expensive and current consuming processors. The larger current consumption results in the need for larger batteries or reduced operational time.
It would be advantageous if a very low processing power method existed for continuously estimating the orientation of an IMU, enabling the IMU to operate on lower performing processors, and using less electrical power to extend the battery life of the system.
It would be advantageous if this low processing power method could compensate for sensor errors such as accelerometers deviating from pointing in the direction of gravity during inertial accelerations, magnetometers that tend to have high jitter noise levels, and gyroscopes that jitter and can cause orientation estimation drift.